Syngas Production from CO2 and H2O via Solid-Oxide Electrolyzer Cells: Fundamentals, Materials, Degradation, Operating Conditions, and Applications

Highly efficient coelectrolysis of CO2/H2O into syngas (a mixture of CO/H2), and subsequent syngas conversion to fuels and value-added chemicals, is one of the most promising alternatives to reach the corner of zero carbon strategy and renewable electricity storage. This research reviews the current state-of-the-art advancements in the coelectrolysis of CO2/H2O in solid oxide electrolyzer cells (SOECs) to produce the important syngas intermediate. The overviews of the latest research on the operating principles and thermodynamic and kinetic models are included for both oxygen-ion- and proton-conducting SOECs. The advanced materials that have recently been developed for both types of SOECs are summarized. It later elucidates the necessity and possibility of regulating the syngas ratios (H2:CO) via changing the operating conditions, including temperature, inlet gas composition, flow rate, applied voltage or current, and pressure. In addition, the sustainability and widespread application of SOEC technology for the conversion of syngas is highlighted. Finally, the challenges and the future research directions in this field are addressed. This review will appeal to scientists working on renewable-energy-conversion technologies, CO2 utilization, and SOEC applications. The implementation of the technologies introduced in this review offers solutions to climate change and renewable-power-storage problems.

Root Cause Analysis of Degradation in Protonic Ceramic Electrochemical Cell with Interfacial Electrical Sensors Using Data-Driven Machine Learning

Protonic ceramic electrochemical cells (PCECs) offer promising paths for energy storage and conversion. Despite considerable achievements made, PCECs still face challenges such as physiochemical compatibility between componenets and suboptimal solid-solid contact at the interfaces between the electrolytes and electrodes. In this study, a novel approach is proposed that combines in situ electrochemical characterization of interfacial electrical sensor embedded PCECs and machine learning to quantify the contributions of different cell components to total degradation, as well as to predict the remaining useful life. The experimental results suggest that the overpotential induced by the oxygen electrode is 48% less than that of oxygen electrode/electrolyte interfacial contact for up to 1171 h. The data-driven machine learning simulation predicts the RUL of up to 2132 h. The root cause of degradation is overpotential increase induced by oxygen electrode, which accounts for 82.9% of total cell degradation. The success of the failure diagnostic model is demonstrated by its consistency with degradation modes that do not manifest in electrolysis fade during early real operations. This synergistic approach provides valuable insights into practical failure diagnosis of PCECs and has the potential to revolutionize their development by enabling improved performance prediction and material selection for enhanced durability and efficiency.